Data Exporter
Data Exporter is currently in Beta. To enable it for your account, contact your Finout customer success manager or email [email protected].
Overview
Data Exporter automatically delivers your Finout cost data to your own Amazon S3 bucket every day, in Parquet format, ready to load into any BI tool, analytics platform, or data pipeline.
Instead of manually exporting reports, Data Exporter runs on a daily schedule and writes enriched cost data — including your Virtual Tags and reallocation rules — directly to an S3 path of your choosing.
Exported data is enriched by Finout. It includes Virtual Tags and all cost transformations applied in your Data Explorer analysis — not just raw billing data.
What you get
Daily Parquet files written to your S3 bucket automatically
Data enriched with your Finout Virtual Tags and dimensions
Up to 3 months of historical backfill on first run
Automatic re-export of any days where underlying data changed
Step 1 — Create a Data Explorer Analysis
The export is based on a Data Explorer analysis, Finout's multi-dimensional reporting tool. The analysis defines the dimensions, filters, measurements, and Virtual Tags included in each daily export file.
Create your analysis
In the Finout console, navigate to Data Explorer in the left-hand menu.
Click New Data Explorer.
Give it a descriptive name.
Add your dimensions and measurements.
Apply any filters to scope the data (for example, specific cost centers or tag values).
Click Save.
Important constraints
Each analysis can include up to 20 dimensions. Plan your dimension selection accordingly before connecting the analysis to an export.
Once a Data Explorer analysis is connected to an active export, the analysis itself is locked for editing. Note that the objects it references — such as Virtual Tags — remain editable, and changes to them are reflected in subsequent exports.
Up to 5 analyses can be scheduled as S3 exports per account.
Step 2 — Configure Your S3 Endpoint
Data Exporter writes to your S3 bucket through an Amazon S3 Bucket Endpoint configured in Read and Write mode.
If you don't already have a Read and Write S3 endpoint, follow the Amazon S3 Bucket Endpoint guide to create one. Make sure to:
Select Read and Write under Bucket Access
Use the Read and Write IAM policy from that guide
Once the endpoint is created and tested, return here for Step 3.
A single Read and Write endpoint can be reused for multiple Data Exporter exports — each export writes to a different sub-path inside the bucket prefix.
Step 3 — Share Your Configuration with Finout
Once your Data Explorer analysis and S3 endpoint are ready, send the following details to your Finout customer success manager to activate the export:
Data Explorer ID
The unique ID of the analysis to export. To find it: open Data Explorer, click the three-dot menu on your analysis, and select Copy Data Explorer ID.
Export Name
A standalone label for the export. This is not the Data Explorer analysis name — you provide it separately, and it is used as-is in your S3 path (see Output File Location). Spaces and case are preserved. Avoid characters that S3 object keys don't support (for example, apostrophes and backticks).
Endpoint Name
The name of the S3 endpoint you configured in Step 2.
Finout configures the export on your behalf and confirms once the first run is scheduled.
Understanding the Export Output
Output file location
Each day, Finout writes one or more Parquet files to the following path in your bucket:
For example, if your Export Name is Finout Cost Report, a daily file lands at:
What's in each file
Columns reflect the dimensions and measurements you defined in your Data Explorer analysis.
Virtual Tags appear as dedicated columns — pre-applied by Finout's enrichment engine.
Data is partitioned by date, with one folder per day.
Historical data and backfill
First run
Finout exports up to 3 months of historical data, then keeps it up to date daily. If longer timeframe is needed, please reach out to support.
Recent days
The most recent 2 days are always refreshed to capture late-arriving billing updates.
Billing changes
If billing data changes for any day within the past 3 months, the affected days are re-exported automatically.
Virtual Tag changes
If a Virtual Tag used in the report is modified, the previous 3 months are re-exported automatically.
No changes
Days with no changes are not re-exported, keeping the process efficient.
FAQs
Can I export multiple analyses to the same bucket?
Yes. You can configure up to 5 scheduled S3 exports per account. Each analysis can write to the same bucket using a different prefix path, keeping datasets organized and separate.
Can I change my Data Explorer analysis after scheduling an export?
Not while the export is active. The analysis configuration is locked to ensure export consistency.
Can I use the same S3 bucket I already use for Finout telemetry or billing data?
Yes — as long as the IAM role has the required write permissions and the prefix paths do not conflict. We recommend using a dedicated prefix (for example, finout/data-exporter/) to keep exports organized.
What file format are the exports in?
All files are exported in Parquet — a columnar format optimized for analytics. Parquet files load directly into tools like Athena, Snowflake, BigQuery, Databricks, dbt, and most BI platforms.
Can I edit or delete an S3 endpoint after creating it?
Not at the moment. If you need a different endpoint, create a new one. Contact your customer success manager or [email protected] if changes are needed.
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